Search

Smart pharmaceutical systems are emerging as integrated therapeutic platforms that combine physiological sensing, algorithmic interpretation, and automated drug release. They mark a shift from passive delivery technologies toward systems that can respond to changing biological states in near real time. Their promise lies in reducing therapeutic delay, personalising dose adjustment, and extending pharmacotherapy beyond fixed schedules and clinician-mediated titration. The central challenge is that therapeutic intelligence changes the risk profile of pharmaceutical products. A delivery system that senses inaccurately, computes incorrectly, or actuates unpredictably can convert a pharmacological benefit into an autonomous harm pathway. This makes safety assurance inseparable from system architecture, rather than a downstream verification step. The review identifies a recurring sense–control–deliver architecture, but argues that this architecture remains unevenly mature. Glucose-responsive and automated insulin systems provide the strongest clinical evidence, whereas multi-analyte drug monitoring, implantable autonomous platforms, and reinforcement-learning controllers remain closer to proof-of-concept or early translational validation. Four tables organise the system logic, sensor landscape, feedback-control approaches, and safety oversight framework. The review concludes that smart pharmaceutical systems should not be judged solely by pharmacokinetic precision or device performance. Their clinical legitimacy will depend on robust control under uncertainty, interpretable autonomy, resilient human oversight, and regulatory pathways that can evaluate integrated drug–device–software behaviour. Safe therapeutic autonomy will require co-development of engineering validation, clinical governance, and patient-centred design.

The clinical success of mRNA–lipid nanoparticle vaccines transformed lipid nanoparticle technology from a specialised drug delivery field into a central modality for modern biopharmaceutical development. That success demonstrated that nucleic acid therapeutics can be manufactured, distributed, and deployed at unprecedented speed when formulation science, process engineering, and regulatory urgency align. Yet the same success also exposed how dependent LNP products remain on tightly constrained composition, process history, and cold-chain stability. The central problem is that processes optimised rapidly under pandemic conditions do not automatically constitute robust manufacturing platforms. Many LNP processes remain product-specific, empirically tuned, and sensitive to changes in lipid composition, aqueous phase conditions, mixing geometry, and downstream handling. The language of “platform” is therefore often stronger than the underlying evidence for generalisable process robustness. The review maps the structural and functional logic of LNP platforms, evaluates how mRNA delivery requirements shaped formulation choices, and assesses preclinical and manufacturing evidence across laboratory, preclinical, and scalable production contexts. It identifies recurrent fragility points including mixing sensitivity, particle heterogeneity, aggregation, mRNA degradation, storage instability, and incomplete comparability evidence after process change. Five tables summarise platform design, mRNA delivery requirements, manufacturing evidence, fragility points, and a system design strategy for robust LNP production. The post-mRNA era requires a shift from emergency product development to platform-centred system design. LNP manufacturing must become modular, measurable, scalable, and quality-resilient rather than merely reproducible under narrowly defined conditions. Achieving this transition is essential if LNP technologies are to move beyond COVID-19 vaccines into broader therapeutic applications and more equitable global health deployment.

Advanced pharmaceutical technologies are reshaping the meaning of a dosage form. Products such as personalised 3D-printed tablets, long-acting injectable depots, implantable systems, nanoparticulate carriers, and digitally enabled drug-device combinations no longer fit neatly within the traditional categories of tablet, capsule, or simple injection. Their performance depends not only on chemical composition, but also on architecture, spatial distribution, release programming, device function, and sometimes digital feedback. The regulatory challenge is that evidence standards for pharmaceutical products were largely built around assumptions of batch uniformity, reproducible manufacturing, conventional dissolution, standardised stability testing, and population-level bioequivalence. These assumptions remain essential for many products, but they may be insufficient when the dosage form is personalised, structurally heterogeneous, programmable, implantable, or integrated with sensors. This creates uncertainty for both regulators and developers because the critical evidence needed to demonstrate quality, safety, and performance is not always clearly defined. This review critically examines how current regulatory expectations apply to non-traditional dosage systems and where they fail to capture technology-specific risks. It focuses on evidence standards across chemistry, manufacturing, and controls; non-clinical performance testing; clinical evaluation; and post-market evidence generation. The aim is not to propose lower evidentiary thresholds, but to argue for standards that are better aligned with the mechanisms by which advanced dosage systems achieve therapeutic performance. The review concludes that regulatory science must move from a one-size-fits-all model toward a flexible, risk-proportionate system for advanced pharmaceutical technologies. Such a system should preserve high standards for patient protection while allowing evidence requirements to vary according to product complexity, novelty, exposure duration, reversibility, and clinical uncertainty. International coordination, structured regulator-innovator dialogue, and post-market learning will be essential to prevent regulatory evidence standards from lagging behind pharmaceutical innovation.

The pharmaceutical industry is a significant contributor to environmental pollution, yet the sustainability of pharmaceutical technologies themselves has received less sustained attention than clinical efficacy, quality assurance, manufacturability, and cost. Pharmaceutical products are commonly evaluated through therapeutic performance and regulatory compliance, while the material, energy, solvent, water, packaging, and waste implications of their production and disposal remain secondary. This imbalance is no longer defensible as medicines become embedded within wider debates on planetary health, industrial decarbonisation, chemical pollution, and responsible innovation. Current pharmaceutical technology paradigms often depend on linear manufacturing models in which raw materials, solvents, excipients, packaging components, and delivery devices move through production and use before entering waste streams. This model is particularly problematic where complex formulations, multi-material packaging, single-use components, and persistent active substances create environmental burdens that are difficult to recover or neutralise. The problem is not only the presence of pharmaceuticals in the environment, but also the technological logic that normalises excess material throughput as an acceptable cost of product performance. This critical review examines sustainable pharmaceutical technologies through three connected lenses: green manufacturing, excipient burden, and circular design principles. Green manufacturing addresses how pharmaceutical products are synthesised, processed, purified, and scaled. Excipient burden focuses on the hidden environmental and functional load created by supposedly inactive formulation ingredients. Circular design principles extend the discussion beyond production efficiency toward products, packaging, and delivery systems designed for reduction, recovery, reuse, and responsible end-of-life management. The review identifies that continuous manufacturing, flow chemistry, process intensification, biocatalysis, solvent reduction, process mass intensity, and life-cycle assessment provide important but incomplete routes toward greener pharmaceutical production. It also shows that excipients, packaging, and drug delivery systems remain under-theorised in sustainability debates despite their cumulative contribution to material intensity, environmental persistence, and disposal complexity. Five tables present green manufacturing technologies, excipient burden data, circular design principles, environmental risks, and implementation barriers. The central conclusion is that sustainable pharmaceutical technology requires a systems-level transition rather than a collection of isolated green substitutions. Genuine sustainability will depend on integrating green manufacturing with excipient stewardship, circular product design, environmental risk reduction, regulatory adaptation, and cross-sector accountability. The field must therefore move from sustainability as a supplementary efficiency concern toward sustainability as a core design principle of pharmaceutical innovation.

Advanced drug delivery systems have long promised to transform therapy by improving biodistribution, reducing toxicity, enabling intracellular delivery, extending exposure, and opening therapeutic spaces that conventional dosage forms cannot reach. Yet the field remains marked by a persistent translation paradox: thousands of sophisticated carrier systems are reported in the literature, while only a small fraction progress into durable clinical products. This gap is usually explained through biological complexity, manufacturing difficulty, regulatory uncertainty, or inadequate preclinical models. This critical perspective proposes that these explanations, although important, are incomplete. A deeper systemic factor is technological lock-in, defined here as the self-reinforcing dominance of specific drug delivery platforms that shape what researchers, funders, manufacturers, regulators, and companies consider technically feasible and translationally credible. Once a platform accumulates expertise, protocols, supply chains, regulatory familiarity, and publication momentum, alternatives may struggle to compete even when they offer potentially superior solutions. The central argument is that technological lock-in contributes to translational failure by narrowing the drug delivery imagination. Instead of asking which delivery architecture is best suited to a given biological, clinical, manufacturing, and regulatory problem, the field often asks how an incumbent platform can be modified to fit yet another therapeutic challenge. This platform-first logic can lead to repeated optimisation of familiar systems while more disruptive or simpler design spaces remain underexplored. The article critically examines the assumptions that sustain dominant platforms in advanced drug delivery. These assumptions include beliefs that increasing carrier complexity necessarily improves therapeutic performance, that certain materials possess broad translational privilege, that murine and in vitro models can adequately predict human outcomes, and that incremental optimisation is less risky than platform diversification. The perspective argues that these assumptions are not merely technical claims but institutional habits that stabilise lock-in. The proposed conceptual model links critical assumptions, technological lock-in, platform dependency, innovation constraint, and translational failure in a self-reinforcing cycle. In this model, failure does not necessarily disrupt dominant platforms; paradoxically, it may intensify dependence on them because they remain the most familiar, fundable, publishable, manufacturable, and regulatable options. Five tables structure the analysis by summarising translational failure evidence, critical assumptions, failure mechanisms, lock-in case examples, and the proposed model. Breaking technological lock-in requires more than improving individual formulations. It requires deliberate diversification of platform portfolios, stronger interrogation of inherited assumptions, translational assessment that rewards fit-for-purpose simplicity, and innovation policies that lower the cost of exploring alternative delivery architectures. A more resilient advanced drug delivery ecosystem should treat platform diversity not as inefficiency, but as insurance against repeated translational failure.